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Prediction of Consumed Electric Power on a MQL Milling Process using a Kriging Meta-Model

장덕용, 정지현, 석종원

Prediction of Consumed Electric Power on a MQL Milling Process using a Kriging Meta-Model

Duk-yong Jang, Jeehyun Jung, Jongwon Seok
JKSPE 2015;32(4):353-358.
Published online: April 1, 2015
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Energy consumption reduction has become an important key word in manufacturing that can be achieved through the efficient and optimal use of raw materials and natural resources, and minimization of the harmful effects on nature or human society. The successful implementation of this concept can only be possible by considering a product"s entire life cycle and even its disposal from the early design stage. To accomplish this idea with milling, minimum quantity lubrication (MQL) strategies and cutting conditions are analyzed through process modeling and experiments. In this study, a model to predict the cutting energy in the milling process is used to find the cutting conditions, which minimize the cutting energy through a Kriging meta-modeling process. The MQL scheme is developed first to reduce the amount of cutting oil and costs used in the cutting process, which is then employed for the entire modeling and experiments.

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Prediction of Consumed Electric Power on a MQL Milling Process using a Kriging Meta-Model
J. Korean Soc. Precis. Eng.. 2015;32(4):353-358.   Published online April 1, 2015
Download Citation

Download a citation file in RIS format that can be imported by all major citation management software, including EndNote, ProCite, RefWorks, and Reference Manager.

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Prediction of Consumed Electric Power on a MQL Milling Process using a Kriging Meta-Model
J. Korean Soc. Precis. Eng.. 2015;32(4):353-358.   Published online April 1, 2015
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